Tag Archive : Technology

It is a time in history when devices that rove around the globe is empowered with a plethora of multi-functional technologies that can capture gestures, show clear readings to proximity temperature, etc. the list just goes on.

Internet of things is to be held accountable for such versatility, in bits and pieces, but does that clearly throw light upon the importance of this technology? With the ‘Big Bang’ of data and connected devices (the key foundation of IoT), the business sector is all warmed up.

However, the point of discussion over here is that in the absence of understanding to interpret data, and comprehend which one should take a lower priority, IoT is nothing but an unstructured flow of ineffective data.

The absence of AI deployment in IoTenabled devices stands as a ball and chain towards the blistering development of technology that put a veil on the real prize of humankind the astonishing transformation prospects, which IoT offers.

In support of this argument, market survey reports state that more and more organizations have turned to AI to not only improve but also change their business operations.

AI boosts IoT enabled devices

If a company has picked up pace in recent years, it is quite obvious to say that the business organization has inculcated rightful amalgamation of AI and IoT. For instance, Uber uses AI to connect the right passenger with the driver, thanks to customer behavior recognition and autonomous driving approach of data science.

For a highly operated IoT device, in order to comprehend what’s really taking place around a device and to respond dynamically, AI is the key tool. For this, AI needs to be deployed in the right manner, in a bid to realize the IoT offered benefits.

Key Considerations for using AI in IoT

To incorporate AI and derive maximum value from the data IoT makes available, business needs to consider some key steps.

Consider how to incorporate AI training into the process

Ensure the AI systems are constantly refined and enhanced

To conclude with AI in IoT

AI training is as crucial as algorithmic coding for traditional systems, however, in the present scenario that is a worldwide challenge.

With the right training model, IoT models can balance a pragmatic approach toward devices that have human intervention and contribution at the forefront.

If your business has IoT enabled devices, it is quite likely that you will aim to upgrade it with AI, but only with the helping hand of a professional.

As far as the fragment of human imagination travels, speed that up into hundred times more and still, you would not be in calculative terms of understanding to what extent can modern technology lead up to! Barring all limitations, technology evolution in the 21st century seems to be unfolding in such an escalating manner that even the direst of things are not impossible attainments for Scientists and Data Engineers.

Highlighting under this context, one of the massively growing and pervading all sectors of business and lives, is the emergence of Artificial Intelligence. With the sarong demands of the youth, business professionals, and corporate leaders for more upgraded versions of the technology, Artificial Intelligence does complete justice to the aforementioned productively. Additionally, the complimenting elements of more expediency, more flexibility, and more ease of use with AI make it even more incredible.

Here are few of the most in-trend technologies accelerated by artificial intelligence:

Deep Learning

Eminently categorized as one of the best forms of Artificial Intelligence, Deep Learning performs developmental actions that produce algorithms known as artificial Neural Networks. The base model of this has been stimulated by the human brain function and structure. Amplifying much ahead than the equivalent progress of Machine Learning, Deep Learning has outdone 40 fold times more between the years 2015 and 2018. Sectors like autonomous vehicles, computer vision, and automatic text generation have Artificial Intelligence technology at its peak with deep learning being its core use of operative mode.

Facial Recognition

Being regarded as the future of Artificial Intelligence, facial recognition is a colossal breakthrough in the field of technology. Its mounting popularity and progressive growth in the market leaves no room for doubt about its current functionality. With the advent of the year 2019, facial recognition takes giant leaps and dominates the urban mass with its significant power of technological autocracy. To state an example from the current hour, AI-based fun application known by the name FaceApp is a direct testimony of the factual existence of AI’s exponential growth. The app analyzes your face and shows your aged look due to the app’s functionality based on AI + Analytics and ML.

Cloud

Enhancing and streamlining business operations and managing data storing systems superfluously, the cloud is a fantastic example of AI-empowered technologies. The global expansions of MNC’s have pushed forward the occurrence of the largest public cloud adoption in the year 2019.

Therefore, transformations of businesses digitally have laddered up to a whole new level that the future predictions are even challenging to fathom. Building a concrete reputation as a leading AI-empowered business solution provider, SPIN Strategy is a name that is going to be your need of the hour. With a highly qualified and certified competent team of engineers and Data Scientists, SPIN Strategy understands the essence of the AI revolution and its impact on business and leaves no stone turned to improvise operational excellence.

It is an inevitable fact and goes without saying that on account of the very nature of data, technology, and analytics that is always at odds for different enterprises, optimal Big Data Deployment strategy may sing a different tune for other business. Period!

This fact-based truth opens the door for strategies, customized only for particular organizations with the pre-conceived motive to deploy Big Data technologies minus any kind of fall out or interruption.

Sounds soothing to the ears?

Note: Before kicking off with the ‘deployment’ process, it comes as a de rigueur step to conduct a detailed evaluation of integration, governance, security, processes, and interoperability, in a bid to reap the pleasure of a seamless Big Data implementation.

Let’s dig deep and get to the pulse of new age Big Data architecture and its deployments know-how for a better understanding.

Age of Big Data Technology

Thanks to our good fortune, we live and breathe in an era of Big Data Analytics, where business enterprises go that extra mile to find ways to harness volumes of unstructured data efficiently.

Business organizations these days take the helping hand from analytics to convert data into valuable insights to pave the way for enhanced operations and informed business decisions.

Riding on the back of intelligent algorithms, organizations give birth to smart data, which can evaluate patterns and signals to help business leaders make informed decisions and thereby cut down costs to perk up profit margins.

However, such an objective is not a walk in the park and requires the assistance of requisite technology within Big Data Environments.

Taking the plunge in the absence of required knowledge and an infallible Big Data strategy is bound to witness a dead-end.

Imperfect deployment road-maps and wrong decisions which can drain out the resources and budget and adversely impact the business performance further gives clarity on the gravity of the situation.

So it is important to understand the Big Data Deployment framework for effective execution.

Big Data Deployment Framework

Out of the lot, there are certain primary factors that manipulate the mammoth decision of employing Big Data technology in a business enterprise.

Such factors include:

• The existence of traditional/non-traditional data in the system
• Presence of low latency data
• Delving into new analytics algorithms
• The requirement for real-time insights

Pillars of Big Data architecture- Analytics, Data, and Technology

Data
There can be no objection to the fact that ‘Data’ is the very heart of technology, analytics, and strategic decision making.

Based on the volume, shape, and latency the type of Big Data technology to be deployed in a company is determined.

Precise mapping of data properties, frequencies, and sources are tagged as significant angles while devising the development strategy.

To make the most of analytics, an amalgamation of traditional technologies and a distributed environment for Big Data can possibly the best road open for some companies to accomplish their business objective.

TechnologyFor most business leaders, it is relatable when we quote that ‘the present infrastructure in many companies is limited to minor data problems’.

Close examination of the existing hardware and software can bridge the gap between tradition and modern approach with ace technologies and predominant systems.

Finally Big Data Integration

The whole idea behind the smooth integration of Big Data technologies in the present infrastructure is to achieve no disruption, zero business downtime, and no cost overruns.

For such integration, numerous databases, nodes, and clusters are required to be explored.

At a business enterprise level, cross-project inter-departmental and multi-platform integration of Big Data technologies must be decided at an early stage, since this can be a difficult task to complete later on.

Concluding Note

Like it or not, a comprehensive, rigorous and importunate decision-making is the absolute need of the hour for deploying Big Data Technologies in any company.

Furthermore, the strategy should make amends with the changing landscape of Big Data technologies.

The deployment strategy is more than a certain piece of information jotted down on a piece of paper.

At SPIN, we understand the mechanism to dispose of Big Data strategy within the present infrastructure of a company in order to bring to pass maximum impact (in a positive way).

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